Boosting Multimodal Semantic Understanding by Local Similarity Adaptation and Global Correlation Propagation

2010 ◽  
pp. 148-158 ◽  
Author(s):  
Hong Zhang ◽  
Xiaoli Liu
Keyword(s):  
Local Similarity ◽  
Global Correlation

scholarly journals Local-crosscorrelation elastic full-waveform inversion

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. R897-R908 ◽  
Author(s):  
Zhen-dong Zhang ◽  
Tariq Alkhalifah
Keyword(s):  
Seismic Data ◽  
Weighting Function ◽  
Waveform Inversion ◽  
Local Similarity ◽  
Full Waveform Inversion ◽  
Half Cycle ◽  
The North ◽  
Full Waveform ◽  
Global Correlation ◽  
The Difference

Full-waveform inversion (FWI) in its classic form is a method based on minimizing the [Formula: see text] norm of the difference between the observed and simulated seismic waveforms at the receiver locations. The objective is to find a subsurface model that reproduces the full waveform including the traveltimes and amplitudes of the observed seismic data. However, the widely used [Formula: see text]-norm-based FWI faces many issues in practice. The point-wise comparison of waveforms fails when the phase difference between the compared waveforms of the predicted and observed data is larger than a half-cycle. In addition, amplitude matching is impractical considering the simplified physics that we often use to describe the medium. To avoid these known problems, we have developed a novel elastic FWI algorithm using the local-similarity attribute. It compares two traces within a predefined local time extension; thus, is not limited by the half-cycle criterion. The algorithm strives to maximize the local similarities of the predicted and observed data by stretching/squeezing the observed data. Phases instead of amplitudes of the seismic data are used in the comparison. The algorithm compares two data sets locally; thus, it performs better than the global correlation in matching multiple arrivals. Instead of picking/calculating one stationary stretching/squeezing curve, we used a weighted integral to find all possible stationary curves. We also introduced a polynomial-type weighting function, which is determined only by the predefined maximum stretching/squeezing and is guaranteed to be smoothly varying within the extension range. Compared with the previously used Gaussian or linear weighting functions, our polynomial one has fewer parameters to play around with. A modified synthetic elastic Marmousi model and the North Sea field data are used to verify the effectiveness of the developed approach and also reveal some of its limitations.

scholarly journals Compressed pseudo-SLAM: pseudorange-integrated compressed simultaneous localisation and mapping for unmanned aerial vehicle navigation

2021 ◽  
pp. 1-13
Author(s):  
Jonghyuk Kim ◽  
Jose Guivant ◽  
Martin L. Sollie ◽  
Torleiv H. Bryne ◽  
Tor Arne Johansen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Computational Cost ◽  
Satellite System ◽  
Measurement Unit ◽  
Electronic Systems ◽  
Computationally Efficient ◽  
Global Correlation ◽  
Aerial Vehicle ◽  
Correlation Information ◽  
Global Navigation Satellite

Abstract This paper addresses the fusion of the pseudorange/pseudorange rate observations from the global navigation satellite system and the inertial–visual simultaneous localisation and mapping (SLAM) to achieve reliable navigation of unmanned aerial vehicles. This work extends the previous work on a simulation-based study [Kim et al. (2017). Compressed fusion of GNSS and inertial navigation with simultaneous localisation and mapping. IEEE Aerospace and Electronic Systems Magazine, 32(8), 22–36] to a real-flight dataset collected from a fixed-wing unmanned aerial vehicle platform. The dataset consists of measurements from visual landmarks, an inertial measurement unit, and pseudorange and pseudorange rates. We propose a novel all-source navigation filter, termed a compressed pseudo-SLAM, which can seamlessly integrate all available information in a computationally efficient way. In this framework, a local map is dynamically defined around the vehicle, updating the vehicle and local landmark states within the region. A global map includes the rest of the landmarks and is updated at a much lower rate by accumulating (or compressing) the local-to-global correlation information within the filter. It will show that the horizontal navigation error is effectively constrained with one satellite vehicle and one landmark observation. The computational cost will be analysed, demonstrating the efficiency of the method.

scholarly journals The Study of Multiple Classes Boosting Classification Method Based on Local Similarity

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 37
Author(s):  
Shixun Wang ◽  
Qiang Chen
Keyword(s):  
Image Retrieval ◽  
Loss Function ◽  
Single Mode ◽  
Local Similarity ◽  
Text And Image ◽  
Data Set ◽  
Standard Data ◽  
Weak Learner ◽  
Great Progress ◽  
Data Points

Boosting of the ensemble learning model has made great progress, but most of the methods are Boosting the single mode. For this reason, based on the simple multiclass enhancement framework that uses local similarity as a weak learner, it is extended to multimodal multiclass enhancement Boosting. First, based on the local similarity as a weak learner, the loss function is used to find the basic loss, and the logarithmic data points are binarized. Then, we find the optimal local similarity and find the corresponding loss. Compared with the basic loss, the smaller one is the best so far. Second, the local similarity of the two points is calculated, and then the loss is calculated by the local similarity of the two points. Finally, the text and image are retrieved from each other, and the correct rate of text and image retrieval is obtained, respectively. The experimental results show that the multimodal multi-class enhancement framework with local similarity as the weak learner is evaluated on the standard data set and compared with other most advanced methods, showing the experience proficiency of this method.

scholarly journals Compressed sensing image restoration algorithm based on improved SURF operator

Open Physics ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 1033-1045
Author(s):  
Guodong Zhou ◽  
Huailiang Zhang ◽  
Raquel Martínez Lucas
Keyword(s):  
Compressed Sensing ◽  
Image Restoration ◽  
Feature Vector ◽  
Optimization Method ◽  
Image Feature ◽  
Diffusion Method ◽  
Local Similarity ◽  
Weighting Method ◽  
Data Smoothing ◽  
Restoration Algorithm

Abstract Aiming at the excellent descriptive ability of SURF operator for local features of images, except for the shortcoming of global feature description ability, a compressed sensing image restoration algorithm based on improved SURF operator is proposed. The SURF feature vector set of the image is extracted, and the vector set data is reduced into a single high-dimensional feature vector by using a histogram algorithm, and then the image HSV color histogram is extracted.MSA image decomposition algorithm is used to obtain sparse representation of image feature vectors. Total variation curvature diffusion method and Bayesian weighting method perform image restoration for data smoothing feature and local similarity feature of texture part respectively. A compressed sensing image restoration model is obtained by using Schatten-p norm, and image color supplement is performed on the model. The compressed sensing image is iteratively solved by alternating optimization method, and the compressed sensing image is restored. The experimental results show that the proposed algorithm has good restoration performance, and the restored image has finer edge and texture structure and better visual effect.

scholarly journals Cellular Heterogeneity–Adjusted cLonal Methylation (CHALM) improves prediction of gene expression

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jianfeng Xu ◽  
Jiejun Shi ◽  
Xiaodong Cui ◽  
Ya Cui ◽  
Jingyi Jessica Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cellular Heterogeneity ◽  
Biological Functions ◽  
Global Correlation ◽  
Differentially Methylated Genes ◽  
Promoter Dna Methylation ◽  
Functional Consequences ◽  
Promoter Dna ◽  
Underlying Mechanisms

AbstractPromoter DNA methylation is a well-established mechanism of transcription repression, though its global correlation with gene expression is weak. This weak correlation can be attributed to the failure of current methylation quantification methods to consider the heterogeneity among sequenced bulk cells. Here, we introduce Cell Heterogeneity–Adjusted cLonal Methylation (CHALM) as a methylation quantification method. CHALM improves understanding of the functional consequences of DNA methylation, including its correlations with gene expression and H3K4me3. When applied to different methylation datasets, the CHALM method enables detection of differentially methylated genes that exhibit distinct biological functions supporting underlying mechanisms.

scholarly journals High-resolution isotope stratigraphy of the Lower Ordovician St. George Group of western Newfoundland, Canada: implications for global correlation

2009 ◽  
Vol 46 (6) ◽  
pp. 403-423 ◽  
Author(s):  
Karem Azmy ◽  
Denis Lavoie
Keyword(s):  
High Resolution ◽  
Sea Level ◽  
Sea Level Changes ◽  
Global Correlation ◽  
Lower Ordovician ◽  
Isotope Stratigraphy ◽  
Platform Carbonates ◽  
The Baltic ◽  
Marine Platform ◽  
Bottom To Top

The Lower Ordovician St. George Group of western Newfoundland consists mainly of shallow-marine-platform carbonates (∼500 m thick). It is formed, from bottom to top, of the Watts Bight, Boat Harbour, Catoche, and Aguathuna formations. The top boundary of the group is marked by the regional St. George Unconformity. Outcrops and a few cores from western Newfoundland were sampled at high resolution and the extracted micritic materials were investigated for their petrographic and geochemical criteria to evaluate their degree of preservation. The δ13C and δ18O values of well-preserved micrite microsamples range from –4.2‰ to 0‰ (VPDB) and from –11.3‰ to –2.9‰ (VPDB), respectively. The δ13Ccarb profile of the St. George Group carbonates reveals several negative shifts, which vary between ∼2‰ and 3‰ and are generally associated with unconformities–disconformities or thin shale interbeds, thus reflecting the effect of or link with significant sea-level changes. The St. George Unconformity is associated with a negative δ13Ccarb shift (∼2‰) on the profile and correlated with major lowstand (around the end of Arenig) on the local sea-level reconstruction and also on those from the Baltic region and central Australia, thus suggesting that the St. George Group Unconformity might have likely had an eustatic component that contributed to the development–enhancement of the paleomargin. Other similar δ13Ccarb shifts have been recorded on the St. George profile, but it is hard to evaluate their global extension due to the low resolution of the documented global Lower Ordovician (Tremadoc – middle Arenig) δ13Ccarb profile.

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